Class specific feature selection for identity validation using dynamic signatures

Kumar, D and Unnikrishnan, P 2013, 'Class specific feature selection for identity validation using dynamic signatures', Journal of Biometrics and Biostatistics, vol. 4, no. 2, pp. 1000160-1-1000160-5.

Document type: Journal Article
Collection: Journal Articles

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Title Class specific feature selection for identity validation using dynamic signatures
Author(s) Kumar, D
Unnikrishnan, P
Year 2013
Journal name Journal of Biometrics and Biostatistics
Volume number 4
Issue number 2
Start page 1000160-1
End page 1000160-5
Total pages 5
Publisher Online Publishing Group
Abstract Classification of the biometrics data for identity validation can be modeled as a single-class problem, where the identity is confirmed by comparing the biometrics of the unknown person with those of the claimed identity. However, current feature selection techniques do not differentiate between single-class and multi-class problems when determining the suitable feature set and select the feature-set that is suitable for representing or discriminating for all the available classes. This may not be the best representation of the biometrics data of an individual because different people may have differences in the most suitable features to represent their biometrical data. In this paper, a class-specific feature selection method has been proposed and experimentally validated using dynamic signatures. This method is based on the coefficient of variance within the feature set, where the features with smaller variance are selected and the ones with larger variance are rejected. The proposed technique was compared with the other feature selection methods, and the results show that a significant improvement in the classification accuracy, specificity and sensitivity was obtained when using class-specific feature selection.
Subject Pattern Recognition and Data Mining
Expert Systems
Keyword(s) Dynamic signature
feature selection
identity validation
DOI - identifier 10.4172/2155-6180.1000160
Copyright notice © 2013 Kumar D, et al.
ISSN 2155-6180
Additional Notes Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
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